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Application of Genetic Algorithm in Functional Area Layout of Railway Logistics Park

机译:遗传算法在铁路物流园区功能区布局中的应用

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As a new type of logistics network nodes, the logistics park is a significant part of the logistics system. Planning and constructing logistics parks scientifically is conducive to not only the construction of modern logistics environment but also the realization of the parks’ function and the whole benefit of the logistics system. Realization of the optimal layout of functional areas with appropriate methods is the basis of logistics park planning and construction. Accordingly, the internal layout of each functional area can be further designed. In this paper, the genetic algorithm is adopted to solve the functional areas layout optimization problem of the railway logistics parks. After getting the comprehensive relationship chart of the different functional areas, the paper solved the layout problem with mathematical methods instead of the traditional manual adjustment method. Combined with relevant constraint conditions, the paper constructed the model taking the maximal arithmetic product of comprehensive relationship and adjacency degree as the objective function. Then the article coded with Matlab based on genetic algorithm. The model was testified to its feasibility and rationality by a practical illustrative example. In this paper, the functional area layout problem of the logistics park was regarded as a mathematical optimization problem, so that the uncertainties of layout affected by subjective factors was reduced to a certain extent combining qualitative analysis with quantitative analysis. The application of genetic algorithm in the layout optimization model greatly improved the quantifiable accuracy which provided a new thought for the functional areas layout of railway logistics parks.
机译:作为新型的物流网络节点,物流园区是物流系统的重要组成部分。科学地规划建设物流园区,不仅有利于现代物流环境的建设,而且有利于园区功能的实现和物流体系的整体效益。用适当的方法实现功能区的优化布局,是物流园区规划建设的基础。因此,可以进一步设计每个功能区域的内部布局。本文采用遗传算法解决铁路物流园区功能区布局优化问题。在获得了不同功能区域的综合关系图之后,本文用数学方法代替了传统的手动调整方法来解决布局问题。结合相关约束条件,以综合关系和邻接度的最大算术积为目标函数,构建了模型。然后基于遗传算法,用Matlab对本文进行了编码。通过一个实际的例子验证了该模型的可行性和合理性。本文将物流园区的功能区布局问题作为数学优化问题,结合定性分析和定量分析,在一定程度上降低了主观因素影响的布局不确定性。遗传算法在布局优化模型中的应用大大提高了量化精度,为铁路物流园区功能区布局提供了新思路。

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